Overview

Brought to you by YData

Dataset statistics

Number of variables24
Number of observations1177898
Missing cells7362621
Missing cells (%)26.0%
Duplicate rows348
Duplicate rows (%)< 0.1%
Total size in memory207.8 MiB
Average record size in memory185.0 B

Variable types

Categorical8
Text5
Numeric6
DateTime1
Boolean1
URL3

Dataset

DescriptionEDA of TMDB Movie Dataset. Dataset Source: Asaniczka, and themoviedb.org. (2025). Full TMDB Movies Dataset 2024 (1M Movies) [Data set]. Kaggle. https://doi.org/10.34740/KAGGLE/DSV/10601279
URLhttps://github.com/ekaterinaleks/RAG
Copyright(c) ekaterinaleks 2025

Variable descriptions

idUnique identifier for each movie
titleTitle of the movie
vote_averageAverage vote or rating given by viewers
vote_countTotal count of votes received for the movie
statusThe status of the movie (e.g., Released, Rumored, Post Production, etc.)
release_dateDate when the movie was released
revenueTotal revenue generated by the movie
runtimeDuration of the movie in minutes
adultIndicates if the movie is suitable only for adult audiences
backdrop_pathURL of the backdrop image for the movie
budgetBudget allocated for the movie
homepageOfficial homepage URL of the movie
imdb_idIMDb ID of the movie
original_languageOriginal language in which the movie was produced
original_titleOriginal title of the movie
overviewBrief description or summary of the movie
popularityPopularity score of the movie
poster_pathURL of the movie poster image
taglineCatchphrase or memorable line associated with the movie
genresList of genres the movie belongs to
production_companiesList of production companies involved in the movie
production_countriesList of countries involved in the movie production
spoken_languagesList of languages spoken in the movie
keywordsKeywords associated with the movie

Alerts

Dataset has 348 (< 0.1%) duplicate rowsDuplicates
id has a high cardinality: 1177061 distinct values High cardinality
imdb_id has a high cardinality: 611141 distinct values High cardinality
original_language has a high cardinality: 174 distinct values High cardinality
genres has a high cardinality: 13586 distinct values High cardinality
production_companies has a high cardinality: 210482 distinct values High cardinality
production_countries has a high cardinality: 10204 distinct values High cardinality
spoken_languages has a high cardinality: 7121 distinct values High cardinality
status is highly imbalanced (92.0%) Imbalance
adult is highly imbalanced (54.6%) Imbalance
original_language is highly imbalanced (57.9%) Imbalance
genres is highly imbalanced (55.3%) Imbalance
production_countries is highly imbalanced (59.8%) Imbalance
spoken_languages is highly imbalanced (63.1%) Imbalance
release_date has 204596 (17.4%) missing values Missing
backdrop_path has 868265 (73.7%) missing values Missing
homepage has 1053966 (89.5%) missing values Missing
imdb_id has 565308 (48.0%) missing values Missing
overview has 244823 (20.8%) missing values Missing
poster_path has 379533 (32.2%) missing values Missing
tagline has 1012960 (86.0%) missing values Missing
genres has 479439 (40.7%) missing values Missing
production_companies has 650313 (55.2%) missing values Missing
production_countries has 529788 (45.0%) missing values Missing
spoken_languages has 509889 (43.3%) missing values Missing
keywords has 863715 (73.3%) missing values Missing
vote_count is highly skewed (γ1 = 41.71780838) Skewed
revenue is highly skewed (γ1 = 72.20691263) Skewed
runtime is highly skewed (γ1 = 34.22107114) Skewed
budget is highly skewed (γ1 = 52.62476446) Skewed
popularity is highly skewed (γ1 = 176.4809293) Skewed
id is uniformly distributed Uniform
imdb_id is uniformly distributed Uniform
vote_average has 826468 (70.2%) zeros Zeros
vote_count has 826230 (70.1%) zeros Zeros
revenue has 1156547 (98.2%) zeros Zeros
runtime has 331291 (28.1%) zeros Zeros
budget has 1116074 (94.8%) zeros Zeros
popularity has 148007 (12.6%) zeros Zeros

Reproduction

Analysis started2025-02-14 12:46:46.429628
Analysis finished2025-02-14 12:49:25.334278
Duration2 minutes and 38.9 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

id
Categorical

High cardinality  Uniform 

Unique identifier for each movie

Distinct1177061
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size9.0 MiB
1228816
 
4
1192939
 
4
1223254
 
4
1224040
 
4
1267870
 
4
Other values (1177056)
1177878 

Length

Max length7
Median length6
Mean length6.2773058
Min length1

Unique

Unique1176568 ?
Unique (%)99.9%

Sample

1st row27205
2nd row157336
3rd row155
4th row19995
5th row24428

Common Values

ValueCountFrequency (%)
1228816 4
 
< 0.1%
1192939 4
 
< 0.1%
1223254 4
 
< 0.1%
1224040 4
 
< 0.1%
1267870 4
 
< 0.1%
1229265 4
 
< 0.1%
1236071 4
 
< 0.1%
1258162 4
 
< 0.1%
1252268 4
 
< 0.1%
1256725 4
 
< 0.1%
Other values (1177051) 1177858
> 99.9%

Length

2025-02-14T13:49:25.582361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1228816 4
 
< 0.1%
1209122 4
 
< 0.1%
1247212 4
 
< 0.1%
1241950 4
 
< 0.1%
1254286 4
 
< 0.1%
1208789 4
 
< 0.1%
1223689 4
 
< 0.1%
1192966 4
 
< 0.1%
1202079 4
 
< 0.1%
1200891 4
 
< 0.1%
Other values (1177051) 1177858
> 99.9%

title
Text

Title of the movie

Distinct1008790
Distinct (%)85.6%
Missing13
Missing (%)< 0.1%
Memory size9.0 MiB
2025-02-14T13:49:27.986675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length324
Median length247
Mean length19.899391
Min length1

Unique

Unique945046 ?
Unique (%)80.2%

Sample

1st rowInception
2nd rowInterstellar
3rd rowThe Dark Knight
4th rowAvatar
5th rowThe Avengers
ValueCountFrequency (%)
69038
 
2.4%
2 19858
 
0.7%
live 14610
 
0.5%
love 14499
 
0.5%
3 10114
 
0.4%
life 8065
 
0.3%
story 8044
 
0.3%
night 8040
 
0.3%
big 6655
 
0.2%
world 6636
 
0.2%
Other values (396770) 2660499
94.1%
2025-02-14T13:49:29.656796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

vote_average
Real number (ℝ)

Zeros 

Average vote or rating given by viewers

Distinct5024
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8228851
Minimum0
Maximum10
Zeros826468
Zeros (%)70.2%
Negative0
Negative (%)0.0%
Memory size9.0 MiB
2025-02-14T13:49:29.848195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.5
95-th percentile8
Maximum10
Range10
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation2.9957169
Coefficient of variation (CV)1.6433931
Kurtosis0.051454129
Mean1.8228851
Median Absolute Deviation (MAD)0
Skewness1.2593323
Sum2147172.8
Variance8.9743198
MonotonicityNot monotonic
2025-02-14T13:49:29.989917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 826468
70.2%
6 30699
 
2.6%
5 29923
 
2.5%
10 25562
 
2.2%
7 24418
 
2.1%
8 20045
 
1.7%
4 11811
 
1.0%
2 9647
 
0.8%
5.5 8737
 
0.7%
6.5 8637
 
0.7%
Other values (5014) 181951
 
15.4%
ValueCountFrequency (%)
0 826468
70.2%
0.5 378
 
< 0.1%
0.75 1
 
< 0.1%
0.8 106
 
< 0.1%
0.875 1
 
< 0.1%
0.9 2
 
< 0.1%
1 6537
 
0.6%
1.1 5
 
< 0.1%
1.167 3
 
< 0.1%
1.179 1
 
< 0.1%
ValueCountFrequency (%)
10 25562
2.2%
9.98 1
 
< 0.1%
9.9 9
 
< 0.1%
9.875 1
 
< 0.1%
9.872 1
 
< 0.1%
9.833 6
 
< 0.1%
9.8 121
 
< 0.1%
9.769 1
 
< 0.1%
9.763 1
 
< 0.1%
9.75 22
 
< 0.1%

vote_count
Real number (ℝ)

Skewed  Zeros 

Total count of votes received for the movie

Distinct3598
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.210619
Minimum0
Maximum34495
Zeros826230
Zeros (%)70.1%
Negative0
Negative (%)0.0%
Memory size9.0 MiB
2025-02-14T13:49:30.174395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile15
Maximum34495
Range34495
Interquartile range (IQR)1

Descriptive statistics

Standard deviation312.90154
Coefficient of variation (CV)17.182367
Kurtosis2381.5646
Mean18.210619
Median Absolute Deviation (MAD)0
Skewness41.717808
Sum21450252
Variance97907.374
MonotonicityDecreasing
2025-02-14T13:49:30.372176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 826230
70.1%
1 126986
 
10.8%
2 49245
 
4.2%
3 28744
 
2.4%
4 20841
 
1.8%
5 14940
 
1.3%
6 11098
 
0.9%
7 8548
 
0.7%
8 6765
 
0.6%
9 5650
 
0.5%
Other values (3588) 78851
 
6.7%
ValueCountFrequency (%)
0 826230
70.1%
1 126986
 
10.8%
2 49245
 
4.2%
3 28744
 
2.4%
4 20841
 
1.8%
5 14940
 
1.3%
6 11098
 
0.9%
7 8548
 
0.7%
8 6765
 
0.6%
9 5650
 
0.5%
ValueCountFrequency (%)
34495 1
< 0.1%
32571 1
< 0.1%
30619 1
< 0.1%
29815 1
< 0.1%
29166 1
< 0.1%
28894 1
< 0.1%
27713 1
< 0.1%
27238 1
< 0.1%
26638 1
< 0.1%
25893 1
< 0.1%

status
Categorical

Imbalance 

The status of the movie (e.g., Released, Rumored, Post Production, etc.)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.0 MiB
Released
1149020 
In Production
 
11764
Post Production
 
8973
Planned
 
7433
Rumored
 
400

Length

Max length15
Median length8
Mean length8.0966111
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReleased
2nd rowReleased
3rd rowReleased
4th rowReleased
5th rowReleased

Common Values

ValueCountFrequency (%)
Released 1149020
97.5%
In Production 11764
 
1.0%
Post Production 8973
 
0.8%
Planned 7433
 
0.6%
Rumored 400
 
< 0.1%
Canceled 308
 
< 0.1%

Length

2025-02-14T13:49:30.523255image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-02-14T13:49:30.622696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
released 1149020
96.8%
production 20737
 
1.7%
post 8973
 
0.8%
planned 7433
 
0.6%
rumored 400
 
< 0.1%
canceled 308
 
< 0.1%

release_date
Date

Missing 

Date when the movie was released

Distinct42887
Distinct (%)4.4%
Missing204596
Missing (%)17.4%
Memory size9.0 MiB
Minimum1800-01-01 00:00:00
Maximum2099-11-18 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-02-14T13:49:30.771784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:30.940939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

revenue
Real number (ℝ)

Skewed  Zeros 

Total revenue generated by the movie

Distinct14361
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean684051.42
Minimum-12
Maximum5 × 109
Zeros1156547
Zeros (%)98.2%
Negative1
Negative (%)< 0.1%
Memory size9.0 MiB
2025-02-14T13:49:31.103831image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-12
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5 × 109
Range5 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18468566
Coefficient of variation (CV)26.998797
Kurtosis9722.459
Mean684051.42
Median Absolute Deviation (MAD)0
Skewness72.206913
Sum8.057428 × 1011
Variance3.4108792 × 1014
MonotonicityNot monotonic
2025-02-14T13:49:31.250950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1156547
98.2%
100 463
 
< 0.1%
1 459
 
< 0.1%
10 260
 
< 0.1%
1000 233
 
< 0.1%
10000 172
 
< 0.1%
100000 170
 
< 0.1%
500 160
 
< 0.1%
2 148
 
< 0.1%
5 140
 
< 0.1%
Other values (14351) 19146
 
1.6%
ValueCountFrequency (%)
-12 1
 
< 0.1%
0 1156547
98.2%
1 459
 
< 0.1%
2 148
 
< 0.1%
3 73
 
< 0.1%
4 41
 
< 0.1%
5 140
 
< 0.1%
6 43
 
< 0.1%
7 29
 
< 0.1%
8 26
 
< 0.1%
ValueCountFrequency (%)
4999999999 1
< 0.1%
3000000000 2
< 0.1%
2930000000 1
< 0.1%
2923706026 1
< 0.1%
2800000000 1
< 0.1%
2320250281 1
< 0.1%
2264162353 1
< 0.1%
2068223624 1
< 0.1%
2052415039 1
< 0.1%
2000000000 1
< 0.1%

runtime
Real number (ℝ)

Skewed  Zeros 

Duration of the movie in minutes

Distinct765
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.139993
Minimum-28
Maximum14400
Zeros331291
Zeros (%)28.1%
Negative1
Negative (%)< 0.1%
Memory size9.0 MiB
2025-02-14T13:49:31.388697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-28
5-th percentile0
Q10
median21
Q388
95-th percentile135
Maximum14400
Range14428
Interquartile range (IQR)88

Descriptive statistics

Standard deviation61.584426
Coefficient of variation (CV)1.3064157
Kurtosis6443.8813
Mean47.139993
Median Absolute Deviation (MAD)21
Skewness34.221071
Sum55526103
Variance3792.6415
MonotonicityNot monotonic
2025-02-14T13:49:31.552013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 331291
28.1%
90 30633
 
2.6%
10 18647
 
1.6%
5 18057
 
1.5%
3 17550
 
1.5%
7 16885
 
1.4%
6 16679
 
1.4%
4 15915
 
1.4%
15 15050
 
1.3%
8 14853
 
1.3%
Other values (755) 682338
57.9%
ValueCountFrequency (%)
-28 1
 
< 0.1%
0 331291
28.1%
1 11231
 
1.0%
2 12111
 
1.0%
3 17550
 
1.5%
4 15915
 
1.4%
5 18057
 
1.5%
6 16679
 
1.4%
7 16885
 
1.4%
8 14853
 
1.3%
ValueCountFrequency (%)
14400 1
< 0.1%
13319 1
< 0.1%
12480 1
< 0.1%
9000 1
< 0.1%
7200 1
< 0.1%
5700 1
< 0.1%
5220 1
< 0.1%
4320 1
< 0.1%
3720 1
< 0.1%
2880 1
< 0.1%

adult
Boolean

Imbalance 

Indicates if the movie is suitable only for adult audiences

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.1 MiB
False
1065515 
True
112383 
ValueCountFrequency (%)
False 1065515
90.5%
True 112383
 
9.5%
2025-02-14T13:49:31.638246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

backdrop_path
URL

Missing 

URL of the backdrop image for the movie

Distinct307048
Distinct (%)99.2%
Missing868265
Missing (%)73.7%
Memory size9.0 MiB
/3CxwYgqGtJ6UEGfWUT0gMYCIlFP.jpg
 
157
/pOXuMdKnWO9hK8drDahJVQxILHx.jpg
 
66
/6r2onqJ2S7XhtnU3HbvNmEv8SXK.jpg
 
47
/60t9ckELUGyinDQNDULFDq2i7u7.jpg
 
44
/iWSrR35uVcpsnosxprWIxE3l4f8.jpg
 
43
Other values (307043)
309276 
(Missing)
868265 
ValueCountFrequency (%)
/3CxwYgqGtJ6UEGfWUT0gMYCIlFP.jpg 157
 
< 0.1%
/pOXuMdKnWO9hK8drDahJVQxILHx.jpg 66
 
< 0.1%
/6r2onqJ2S7XhtnU3HbvNmEv8SXK.jpg 47
 
< 0.1%
/60t9ckELUGyinDQNDULFDq2i7u7.jpg 44
 
< 0.1%
/iWSrR35uVcpsnosxprWIxE3l4f8.jpg 43
 
< 0.1%
/vG0YKrbBQcDSFZYDE1zIqGhqpmc.jpg 38
 
< 0.1%
/dEJ9tgpv8Ly9VeH2TW1wAm4gBbY.jpg 31
 
< 0.1%
/3wkhoahQHZRcl7OaKymA2lGPSVg.jpg 27
 
< 0.1%
/rUcFNAwnTFiKtijDlDp8Ukgz48j.jpg 25
 
< 0.1%
/r3RDMpTou68u0dBuhKHcBz2wTel.jpg 24
 
< 0.1%
Other values (307038) 309131
 
26.2%
(Missing) 868265
73.7%
ValueCountFrequency (%)
309633
 
26.3%
(Missing) 868265
73.7%
ValueCountFrequency (%)
309633
 
26.3%
(Missing) 868265
73.7%
ValueCountFrequency (%)
/3CxwYgqGtJ6UEGfWUT0gMYCIlFP.jpg 157
 
< 0.1%
/pOXuMdKnWO9hK8drDahJVQxILHx.jpg 66
 
< 0.1%
/6r2onqJ2S7XhtnU3HbvNmEv8SXK.jpg 47
 
< 0.1%
/60t9ckELUGyinDQNDULFDq2i7u7.jpg 44
 
< 0.1%
/iWSrR35uVcpsnosxprWIxE3l4f8.jpg 43
 
< 0.1%
/vG0YKrbBQcDSFZYDE1zIqGhqpmc.jpg 38
 
< 0.1%
/dEJ9tgpv8Ly9VeH2TW1wAm4gBbY.jpg 31
 
< 0.1%
/3wkhoahQHZRcl7OaKymA2lGPSVg.jpg 27
 
< 0.1%
/rUcFNAwnTFiKtijDlDp8Ukgz48j.jpg 25
 
< 0.1%
/r3RDMpTou68u0dBuhKHcBz2wTel.jpg 24
 
< 0.1%
Other values (307038) 309131
 
26.2%
(Missing) 868265
73.7%
ValueCountFrequency (%)
309633
 
26.3%
(Missing) 868265
73.7%
ValueCountFrequency (%)
309633
 
26.3%
(Missing) 868265
73.7%

budget
Real number (ℝ)

Skewed  Zeros 

Budget allocated for the movie

Distinct5836
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean264086.73
Minimum0
Maximum1 × 109
Zeros1116074
Zeros (%)94.8%
Negative0
Negative (%)0.0%
Memory size9.0 MiB
2025-02-14T13:49:32.038600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum1 × 109
Range1 × 109
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5101983.7
Coefficient of variation (CV)19.319349
Kurtosis5407.8669
Mean264086.73
Median Absolute Deviation (MAD)0
Skewness52.624764
Sum3.1106723 × 1011
Variance2.6030237 × 1013
MonotonicityNot monotonic
2025-02-14T13:49:32.187529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1116074
94.8%
100 2152
 
0.2%
1000 1988
 
0.2%
500 1671
 
0.1%
10000 1630
 
0.1%
5000 1617
 
0.1%
2000 1297
 
0.1%
200 1158
 
0.1%
50 1095
 
0.1%
10 1095
 
0.1%
Other values (5826) 48121
 
4.1%
ValueCountFrequency (%)
0 1116074
94.8%
1 969
 
0.1%
2 400
 
< 0.1%
3 261
 
< 0.1%
4 161
 
< 0.1%
5 644
 
0.1%
6 129
 
< 0.1%
7 116
 
< 0.1%
8 109
 
< 0.1%
9 59
 
< 0.1%
ValueCountFrequency (%)
999999999 1
 
< 0.1%
900000000 1
 
< 0.1%
888000000 1
 
< 0.1%
800000000 1
 
< 0.1%
645654654 1
 
< 0.1%
600000000 2
< 0.1%
540000000 1
 
< 0.1%
500000000 4
< 0.1%
470000000 1
 
< 0.1%
460000000 1
 
< 0.1%

homepage
URL

Missing 

Official homepage URL of the movie

Distinct116260
Distinct (%)93.8%
Missing1053966
Missing (%)89.5%
Memory size9.0 MiB
https://animation.geidai.ac.jp
 
147
http://www.eldoradofilms.com
 
74
https://www.yamidouga.com/
 
63
https://uaebabes.com
 
57
http://www.ufc.com
 
52
Other values (116255)
123539 
(Missing)
1053966 
ValueCountFrequency (%)
https://animation.geidai.ac.jp 147
 
< 0.1%
http://www.eldoradofilms.com 74
 
< 0.1%
https://www.yamidouga.com/ 63
 
< 0.1%
https://uaebabes.com 57
 
< 0.1%
http://www.ufc.com 52
 
< 0.1%
https://www.youtube.com/ 52
 
< 0.1%
https://pinoyflix.to/ 50
 
< 0.1%
http://www.battlefieldhistory.tv 49
 
< 0.1%
http://www.demand-progress.com 44
 
< 0.1%
https://parallaximag.gr/to-5o-panorama-tainion-tou-tmimatos-kinimatografou-tou-apth-erchetai-sto-cinobo-114082 40
 
< 0.1%
Other values (116250) 123304
 
10.5%
(Missing) 1053966
89.5%
ValueCountFrequency (%)
https 76313
 
6.5%
http 47600
 
4.0%
19
 
< 0.1%
(Missing) 1053966
89.5%
ValueCountFrequency (%)
www.youtube.com 9468
 
0.8%
vimeo.com 3613
 
0.3%
www.bbc.co.uk 2035
 
0.2%
www.netflix.com 1602
 
0.1%
www.nikkatsu.com 1556
 
0.1%
youtu.be 1176
 
0.1%
filmfreeway.com 1105
 
0.1%
www.facebook.com 1003
 
0.1%
www.nfb.ca 794
 
0.1%
www.pbs.org 678
 
0.1%
Other values (55370) 100902
 
8.6%
(Missing) 1053966
89.5%
ValueCountFrequency (%)
/ 25340
 
2.2%
13997
 
1.2%
/watch 7945
 
0.7%
/index.php 275
 
< 0.1%
/film/info/ 239
 
< 0.1%
/video 182
 
< 0.1%
/index.html 156
 
< 0.1%
/en/ 155
 
< 0.1%
/films 131
 
< 0.1%
/FAMS_ipac/cclib/search/showBib.jsp 118
 
< 0.1%
Other values (69781) 75394
 
6.4%
(Missing) 1053966
89.5%
ValueCountFrequency (%)
110787
 
9.4%
lang=en 125
 
< 0.1%
share=copy 98
 
< 0.1%
v=7516fd43adaa 59
 
< 0.1%
showCards=1 45
 
< 0.1%
fref=ts 26
 
< 0.1%
locale=en 23
 
< 0.1%
ref_=ext_shr_lnk 21
 
< 0.1%
partner_id=24903038 19
 
< 0.1%
fbclid=IwAR1jSDQd2twJPGTd2bedseZKv17nM7KypVCRgPBxPCc8vpx__L_QzyLrxFA 17
 
< 0.1%
Other values (12221) 12712
 
1.1%
(Missing) 1053966
89.5%
ValueCountFrequency (%)
122632
 
10.4%
/ 133
 
< 0.1%
/extra 31
 
< 0.1%
story 27
 
< 0.1%
1 18
 
< 0.1%
overview 12
 
< 0.1%
home 11
 
< 0.1%
Review 10
 
< 0.1%
/fight 10
 
< 0.1%
/index 9
 
< 0.1%
Other values (935) 1039
 
0.1%
(Missing) 1053966
89.5%

imdb_id
Categorical

High cardinality  Missing  Uniform 

IMDb ID of the movie

Distinct611141
Distinct (%)99.8%
Missing565308
Missing (%)48.0%
Memory size9.0 MiB
tt32094375
 
72
tt13904644
 
29
tt26900526
 
21
tt8657468
 
16
tt23810972
 
15
Other values (611136)
612437 

Length

Max length10
Median length9
Mean length9.1975955
Min length8

Unique

Unique610234 ?
Unique (%)99.6%

Sample

1st rowtt1375666
2nd rowtt0816692
3rd rowtt0468569
4th rowtt0499549
5th rowtt0848228

Common Values

ValueCountFrequency (%)
tt32094375 72
 
< 0.1%
tt13904644 29
 
< 0.1%
tt26900526 21
 
< 0.1%
tt8657468 16
 
< 0.1%
tt23810972 15
 
< 0.1%
tt5719786 13
 
< 0.1%
tt27430909 12
 
< 0.1%
tt29703523 11
 
< 0.1%
tt27048168 10
 
< 0.1%
tt10980608 10
 
< 0.1%
Other values (611131) 612381
52.0%
(Missing) 565308
48.0%

Length

2025-02-14T13:49:32.353754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tt32094375 72
 
< 0.1%
tt13904644 29
 
< 0.1%
tt26900526 21
 
< 0.1%
tt8657468 16
 
< 0.1%
tt23810972 15
 
< 0.1%
tt5719786 13
 
< 0.1%
tt27430909 12
 
< 0.1%
tt29703523 11
 
< 0.1%
tt27048168 10
 
< 0.1%
tt10980608 10
 
< 0.1%
Other values (611131) 612381
> 99.9%

original_language
Categorical

High cardinality  Imbalance 

Original language in which the movie was produced

Distinct174
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size9.0 MiB
en
636925 
fr
68952 
es
 
59864
de
 
55451
ja
 
51229
Other values (169)
305477 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen

Common Values

ValueCountFrequency (%)
en 636925
54.1%
fr 68952
 
5.9%
es 59864
 
5.1%
de 55451
 
4.7%
ja 51229
 
4.3%
zh 40273
 
3.4%
pt 34928
 
3.0%
it 24664
 
2.1%
ru 24168
 
2.1%
ko 13659
 
1.2%
Other values (164) 167785
 
14.2%

Length

2025-02-14T13:49:32.472835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
fr 68952
25.6%
zh 40273
15.0%
pt 34928
13.0%
ru 24168
 
9.0%
cs 11073
 
4.1%
nl 9281
 
3.4%
sv 8826
 
3.3%
tr 8072
 
3.0%
pl 7323
 
2.7%
tl 6663
 
2.5%
Other values (96) 49644
18.4%

original_title
Text

Original title of the movie

Distinct1043177
Distinct (%)88.6%
Missing13
Missing (%)< 0.1%
Memory size9.0 MiB
2025-02-14T13:49:34.439310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length250
Median length211
Mean length18.863229
Min length1

Unique

Unique983361 ?
Unique (%)83.5%

Sample

1st rowInception
2nd rowInterstellar
3rd rowThe Dark Knight
4th rowAvatar
5th rowThe Avengers
ValueCountFrequency (%)
68252
 
2.5%
2 18529
 
0.7%
live 13834
 
0.5%
3 9470
 
0.3%
love 9090
 
0.3%
story 6313
 
0.2%
4 5956
 
0.2%
1 5791
 
0.2%
night 5722
 
0.2%
life 5627
 
0.2%
Other values (532120) 2591625
94.6%
2025-02-14T13:49:35.402870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

overview
Text

Missing 

Brief description or summary of the movie

Distinct906249
Distinct (%)97.1%
Missing244823
Missing (%)20.8%
Memory size9.0 MiB
2025-02-14T13:49:46.622890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1000
Median length804
Mean length268.8359
Min length1

Unique

Unique897905 ?
Unique (%)96.2%

Sample

1st rowCobb, a skilled thief who commits corporate espionage by infiltrating the subconscious of his targets is offered a chance to regain his old life as payment for a task considered to be impossible: "inception", the implantation of another person's idea into a target's subconscious.
2nd rowThe adventures of a group of explorers who make use of a newly discovered wormhole to surpass the limitations on human space travel and conquer the vast distances involved in an interstellar voyage.
3rd rowBatman raises the stakes in his war on crime. With the help of Lt. Jim Gordon and District Attorney Harvey Dent, Batman sets out to dismantle the remaining criminal organizations that plague the streets. The partnership proves to be effective, but they soon find themselves prey to a reign of chaos unleashed by a rising criminal mastermind known to the terrified citizens of Gotham as the Joker.
4th rowIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.
5th rowWhen an unexpected enemy emerges and threatens global safety and security, Nick Fury, director of the international peacekeeping agency known as S.H.I.E.L.D., finds himself in need of a team to pull the world back from the brink of disaster. Spanning the globe, a daring recruitment effort begins!
ValueCountFrequency (%)
film 156239
 
0.7%
125668
 
0.6%
life 115159
 
0.5%
young 97185
 
0.5%
love 81174
 
0.4%
world 74990
 
0.3%
story 73697
 
0.3%
time 70417
 
0.3%
family 57411
 
0.3%
years 53472
 
0.2%
Other values (659087) 20675707
95.8%
2025-02-14T13:49:48.584611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

popularity
Real number (ℝ)

Skewed  Zeros 

Popularity score of the movie

Distinct19888
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2083839
Minimum0
Maximum2994.357
Zeros148007
Zeros (%)12.6%
Negative0
Negative (%)0.0%
Memory size9.0 MiB
2025-02-14T13:49:48.768453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.6
median0.6
Q30.873
95-th percentile3.157
Maximum2994.357
Range2994.357
Interquartile range (IQR)0.273

Descriptive statistics

Standard deviation7.4549393
Coefficient of variation (CV)6.1693469
Kurtosis51065.519
Mean1.2083839
Median Absolute Deviation (MAD)0
Skewness176.48093
Sum1423352.9
Variance55.57612
MonotonicityNot monotonic
2025-02-14T13:49:48.952816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.6 614555
52.2%
0 148007
 
12.6%
1.4 32458
 
2.8%
0.84 9172
 
0.8%
0.65 4459
 
0.4%
0.841 3667
 
0.3%
0.9 2469
 
0.2%
0.651 2066
 
0.2%
1.09 1719
 
0.1%
0.655 1572
 
0.1%
Other values (19878) 357754
30.4%
ValueCountFrequency (%)
0 148007
 
12.6%
0.36 7
 
< 0.1%
0.363 1
 
< 0.1%
0.59 2
 
< 0.1%
0.6 614555
52.2%
0.601 977
 
0.1%
0.602 830
 
0.1%
0.603 633
 
0.1%
0.604 528
 
< 0.1%
0.605 505
 
< 0.1%
ValueCountFrequency (%)
2994.357 1
< 0.1%
2680.593 1
< 0.1%
2020.286 1
< 0.1%
1692.778 1
< 0.1%
1567.273 1
< 0.1%
1547.22 1
< 0.1%
1458.514 1
< 0.1%
1175.267 1
< 0.1%
1111.036 1
< 0.1%
1069.34 1
< 0.1%

poster_path
URL

Missing 

URL of the movie poster image

Distinct793691
Distinct (%)99.4%
Missing379533
Missing (%)32.2%
Memory size9.0 MiB
/wtoKLMm4UvkwvcSwO3XWcs1gJuF.jpg
 
54
/sRs2R6qI9C3Liv3hWrQTdmoSqqp.jpg
 
54
/cWjdh8VTiizYfQp5m6fJi4PDy8w.jpg
 
48
/je3JbUs3OEoYkS6Vd7iv7w6HUPu.jpg
 
45
/qpXweJ0Gbl5OmYZqzNWtDJovF8e.jpg
 
41
Other values (793686)
798123 
(Missing)
379533 
ValueCountFrequency (%)
/wtoKLMm4UvkwvcSwO3XWcs1gJuF.jpg 54
 
< 0.1%
/sRs2R6qI9C3Liv3hWrQTdmoSqqp.jpg 54
 
< 0.1%
/cWjdh8VTiizYfQp5m6fJi4PDy8w.jpg 48
 
< 0.1%
/je3JbUs3OEoYkS6Vd7iv7w6HUPu.jpg 45
 
< 0.1%
/qpXweJ0Gbl5OmYZqzNWtDJovF8e.jpg 41
 
< 0.1%
/nelvhFPqwYhAw8UFF81sDpFZSlD.jpg 39
 
< 0.1%
/9nQJc8M6u7J4LISv44Y9dMbhQTg.jpg 37
 
< 0.1%
/28vbk6H0CeVmT4aJRADatqCFXmR.jpg 36
 
< 0.1%
/AuLuyBTQs0ecbQXnSHwcKRnn6Qo.jpg 34
 
< 0.1%
/44XDqrWNPiBkIT1ixdtLX23LKlQ.jpg 33
 
< 0.1%
Other values (793681) 797944
67.7%
(Missing) 379533
32.2%
ValueCountFrequency (%)
798365
67.8%
(Missing) 379533
32.2%
ValueCountFrequency (%)
798365
67.8%
(Missing) 379533
32.2%
ValueCountFrequency (%)
/sRs2R6qI9C3Liv3hWrQTdmoSqqp.jpg 54
 
< 0.1%
/wtoKLMm4UvkwvcSwO3XWcs1gJuF.jpg 54
 
< 0.1%
/cWjdh8VTiizYfQp5m6fJi4PDy8w.jpg 48
 
< 0.1%
/je3JbUs3OEoYkS6Vd7iv7w6HUPu.jpg 45
 
< 0.1%
/qpXweJ0Gbl5OmYZqzNWtDJovF8e.jpg 41
 
< 0.1%
/nelvhFPqwYhAw8UFF81sDpFZSlD.jpg 39
 
< 0.1%
/9nQJc8M6u7J4LISv44Y9dMbhQTg.jpg 37
 
< 0.1%
/28vbk6H0CeVmT4aJRADatqCFXmR.jpg 36
 
< 0.1%
/AuLuyBTQs0ecbQXnSHwcKRnn6Qo.jpg 34
 
< 0.1%
/44XDqrWNPiBkIT1ixdtLX23LKlQ.jpg 33
 
< 0.1%
Other values (793681) 797944
67.7%
(Missing) 379533
32.2%
ValueCountFrequency (%)
798365
67.8%
(Missing) 379533
32.2%
ValueCountFrequency (%)
798365
67.8%
(Missing) 379533
32.2%

tagline
Text

Missing 

Catchphrase or memorable line associated with the movie

Distinct158388
Distinct (%)96.0%
Missing1012960
Missing (%)86.0%
Memory size9.0 MiB
2025-02-14T13:49:50.254197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length256
Median length231
Mean length45.014363
Min length1

Unique

Unique155447 ?
Unique (%)94.2%

Sample

1st rowYour mind is the scene of the crime.
2nd rowMankind was born on Earth. It was never meant to die here.
3rd rowWelcome to a world without rules.
4th rowEnter the world of Pandora.
5th rowSome assembly required.
ValueCountFrequency (%)
8100
 
1.3%
love 7963
 
1.2%
story 5793
 
0.9%
life 5165
 
0.8%
world 3724
 
0.6%
film 3521
 
0.5%
time 3471
 
0.5%
live 2183
 
0.3%
back 2083
 
0.3%
family 1834
 
0.3%
Other values (67769) 596744
93.2%
2025-02-14T13:49:51.287561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genres
Categorical

High cardinality  Imbalance  Missing 

List of genres the movie belongs to

Distinct13586
Distinct (%)1.9%
Missing479439
Missing (%)40.7%
Memory size9.0 MiB
Documentary
138954 
Drama
109507 
Comedy
60183 
Animation
 
32405
Music
 
25944
Other values (13581)
331466 

Length

Max length173
Median length144
Mean length11.935876
Min length3

Unique

Unique7966 ?
Unique (%)1.1%

Sample

1st rowAction, Science Fiction, Adventure
2nd rowAdventure, Drama, Science Fiction
3rd rowDrama, Action, Crime, Thriller
4th rowAction, Adventure, Fantasy, Science Fiction
5th rowScience Fiction, Action, Adventure

Common Values

ValueCountFrequency (%)
Documentary 138954
 
11.8%
Drama 109507
 
9.3%
Comedy 60183
 
5.1%
Animation 32405
 
2.8%
Music 25944
 
2.2%
Horror 23188
 
2.0%
Drama, Romance 10797
 
0.9%
Comedy, Drama 9689
 
0.8%
Action 8011
 
0.7%
Romance 7905
 
0.7%
Other values (13576) 271876
23.1%
(Missing) 479439
40.7%

Length

2025-02-14T13:49:51.555197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drama 230857
21.0%
documentary 169270
15.4%
comedy 142015
12.9%
animation 58875
 
5.4%
horror 55108
 
5.0%
romance 53845
 
4.9%
music 49899
 
4.5%
thriller 47661
 
4.3%
action 45061
 
4.1%
crime 34087
 
3.1%
Other values (10) 213636
19.4%

production_companies
Categorical

High cardinality  Missing 

List of production companies involved in the movie

Distinct210482
Distinct (%)39.9%
Missing650313
Missing (%)55.2%
Memory size9.0 MiB
Evil Angel
 
2962
ONF | NFB
 
2266
BBC
 
2158
Metro-Goldwyn-Mayer
 
2046
Columbia Pictures
 
1937
Other values (210477)
516216 

Length

Max length708
Median length423
Mean length24.493263
Min length1

Unique

Unique168560 ?
Unique (%)31.9%

Sample

1st rowLegendary Pictures, Syncopy, Warner Bros. Pictures
2nd rowLegendary Pictures, Syncopy, Lynda Obst Productions
3rd rowDC Comics, Legendary Pictures, Syncopy, Isobel Griffiths, Warner Bros. Pictures
4th rowDune Entertainment, Lightstorm Entertainment, 20th Century Fox, Ingenious Media
5th rowMarvel Studios

Common Values

ValueCountFrequency (%)
Evil Angel 2962
 
0.3%
ONF | NFB 2266
 
0.2%
BBC 2158
 
0.2%
Metro-Goldwyn-Mayer 2046
 
0.2%
Columbia Pictures 1937
 
0.2%
Toei Company 1789
 
0.2%
Nikkatsu Corporation 1636
 
0.1%
Universal Pictures 1549
 
0.1%
Paramount 1510
 
0.1%
Warner Bros. Pictures 1502
 
0.1%
Other values (210472) 508230
43.1%
(Missing) 650313
55.2%

Length

2025-02-14T13:49:51.792481image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
productions 76398
 
4.7%
films 76189
 
4.7%
film 64328
 
4.0%
pictures 47335
 
2.9%
entertainment 34577
 
2.1%
studios 19434
 
1.2%
media 15597
 
1.0%
company 15526
 
1.0%
production 13844
 
0.9%
studio 13603
 
0.8%
Other values (101766) 1246237
76.8%

production_countries
Categorical

High cardinality  Imbalance  Missing 

List of countries involved in the movie production

Distinct10204
Distinct (%)1.6%
Missing529788
Missing (%)45.0%
Memory size9.0 MiB
United States of America
182198 
Japan
41700 
United Kingdom
34642 
Germany
33442 
France
33394 
Other values (10199)
322734 

Length

Max length3023
Median length333
Mean length13.558161
Min length4

Unique

Unique7042 ?
Unique (%)1.1%

Sample

1st rowUnited Kingdom, United States of America
2nd rowUnited Kingdom, United States of America
3rd rowUnited Kingdom, United States of America
4th rowUnited States of America, United Kingdom
5th rowUnited States of America

Common Values

ValueCountFrequency (%)
United States of America 182198
 
15.5%
Japan 41700
 
3.5%
United Kingdom 34642
 
2.9%
Germany 33442
 
2.8%
France 33394
 
2.8%
India 20614
 
1.8%
Canada 19616
 
1.7%
Brazil 16540
 
1.4%
Italy 13637
 
1.2%
Spain 11819
 
1.0%
Other values (10194) 240508
20.4%
(Missing) 529788
45.0%

Length

2025-02-14T13:49:52.020591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united 239684
20.1%
states 197155
16.5%
america 197145
16.5%
france 45582
 
3.8%
germany 44085
 
3.7%
japan 43420
 
3.6%
kingdom 42176
 
3.5%
canada 24830
 
2.1%
india 21504
 
1.8%
italy 19125
 
1.6%
Other values (282) 316854
26.6%

spoken_languages
Categorical

High cardinality  Imbalance  Missing 

List of languages spoken in the movie

Distinct7121
Distinct (%)1.1%
Missing509889
Missing (%)43.3%
Memory size9.0 MiB
English
239131 
Japanese
40935 
Spanish
37963 
French
37379 
No Language
29732 
Other values (7116)
282869 

Length

Max length177
Median length7
Mean length8.1796039
Min length3

Unique

Unique4740 ?
Unique (%)0.7%

Sample

1st rowEnglish, French, Japanese, Swahili
2nd rowEnglish
3rd rowEnglish, Mandarin
4th rowEnglish, Spanish
5th rowEnglish, Hindi, Russian

Common Values

ValueCountFrequency (%)
English 239131
20.3%
Japanese 40935
 
3.5%
Spanish 37963
 
3.2%
French 37379
 
3.2%
No Language 29732
 
2.5%
German 28907
 
2.5%
Portuguese 19207
 
1.6%
Russian 17061
 
1.4%
Mandarin 16087
 
1.4%
Italian 15285
 
1.3%
Other values (7111) 186322
 
15.8%
(Missing) 509889
43.3%

Length

2025-02-14T13:49:52.205070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
english 277866
37.4%
french 50530
 
6.8%
spanish 47190
 
6.4%
japanese 44451
 
6.0%
german 38693
 
5.2%
language 30484
 
4.1%
portuguese 21866
 
2.9%
russian 21703
 
2.9%
italian 20534
 
2.8%
mandarin 19567
 
2.6%
Other values (179) 170219
22.9%

keywords
Text

Missing 

Keywords associated with the movie

Distinct180245
Distinct (%)57.4%
Missing863715
Missing (%)73.3%
Memory size9.0 MiB
2025-02-14T13:49:52.952125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length1588
Median length738
Mean length37.552792
Min length1

Unique

Unique166635 ?
Unique (%)53.0%

Sample

1st rowrescue, mission, dream, airplane, paris, france, virtual reality, kidnapping, philosophy, spy, allegory, manipulation, car crash, heist, memory, architecture, los angeles, california, dream world, subconscious
2nd rowrescue, future, spacecraft, race against time, artificial intelligence (a.i.), nasa, time warp, dystopia, expedition, space travel, wormhole, famine, black hole, quantum mechanics, family relationships, space, robot, astronaut, scientist, single father, farmer, space station, curious, space adventure, time paradox, thoughtful, time-manipulation, father daughter relationship, 2060s, cornfield, time manipulation, complicated
3rd rowjoker, sadism, chaos, secret identity, crime fighter, superhero, anti hero, scarecrow, based on comic, vigilante, organized crime, tragic hero, anti villain, criminal mastermind, district attorney, super power, super villain, neo-noir
4th rowfuture, society, culture clash, space travel, space war, space colony, tribe, romance, alien, futuristic, space, alien planet, marine, soldier, battle, love affair, nature, anti war, power relations, joyful
5th rownew york city, superhero, shield, based on comic, alien invasion, superhero team, aftercreditsstinger, duringcreditsstinger, marvel cinematic universe (mcu)
ValueCountFrequency (%)
film 43501
 
3.0%
short 29618
 
2.0%
woman 20569
 
1.4%
gay 18605
 
1.3%
director 16316
 
1.1%
sex 15837
 
1.1%
based 15505
 
1.1%
pornography 12135
 
0.8%
relationship 10747
 
0.7%
comedy 9161
 
0.6%
Other values (37310) 1263495
86.8%
2025-02-14T13:49:53.622163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-02-14T13:49:13.641359image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:48:59.162500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:01.426253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:08.208953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:09.942957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:11.724023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:13.989964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:48:59.576598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:01.759567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:08.490235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:10.252033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:12.009337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:14.360561image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:48:59.963128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:06.858468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:08.761616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:10.568361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:12.299467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:14.709381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:00.294776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:07.238558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:09.040505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:10.842462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:12.573855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:15.011618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:00.628596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:07.559750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:09.356672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:11.142787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:12.860822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:15.290528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:01.046350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:07.891406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:09.659108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:11.444493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-02-14T13:49:13.308540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Missing values

2025-02-14T13:49:20.608438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.

Sample

idtitlevote_averagevote_countstatusrelease_daterevenueruntimeadultbackdrop_pathbudgethomepageimdb_idoriginal_languageoriginal_titleoverviewpopularityposter_pathtaglinegenresproduction_companiesproduction_countriesspoken_languageskeywords
027205Inception8.36434495Released2010-07-15825532764148False/8ZTVqvKDQ8emSGUEMjsS4yHAwrp.jpg160000000https://www.warnerbros.com/movies/inceptiontt1375666enInceptionCobb, a skilled thief who commits corporate espionage by infiltrating the subconscious of his targets is offered a chance to regain his old life as payment for a task considered to be impossible: "inception", the implantation of another person's idea into a target's subconscious.83.952/oYuLEt3zVCKq57qu2F8dT7NIa6f.jpgYour mind is the scene of the crime.Action, Science Fiction, AdventureLegendary Pictures, Syncopy, Warner Bros. PicturesUnited Kingdom, United States of AmericaEnglish, French, Japanese, Swahilirescue, mission, dream, airplane, paris, france, virtual reality, kidnapping, philosophy, spy, allegory, manipulation, car crash, heist, memory, architecture, los angeles, california, dream world, subconscious
1157336Interstellar8.41732571Released2014-11-05701729206169False/pbrkL804c8yAv3zBZR4QPEafpAR.jpg165000000http://www.interstellarmovie.net/tt0816692enInterstellarThe adventures of a group of explorers who make use of a newly discovered wormhole to surpass the limitations on human space travel and conquer the vast distances involved in an interstellar voyage.140.241/gEU2QniE6E77NI6lCU6MxlNBvIx.jpgMankind was born on Earth. It was never meant to die here.Adventure, Drama, Science FictionLegendary Pictures, Syncopy, Lynda Obst ProductionsUnited Kingdom, United States of AmericaEnglishrescue, future, spacecraft, race against time, artificial intelligence (a.i.), nasa, time warp, dystopia, expedition, space travel, wormhole, famine, black hole, quantum mechanics, family relationships, space, robot, astronaut, scientist, single father, farmer, space station, curious, space adventure, time paradox, thoughtful, time-manipulation, father daughter relationship, 2060s, cornfield, time manipulation, complicated
2155The Dark Knight8.51230619Released2008-07-161004558444152False/nMKdUUepR0i5zn0y1T4CsSB5chy.jpg185000000https://www.warnerbros.com/movies/dark-knight/tt0468569enThe Dark KnightBatman raises the stakes in his war on crime. With the help of Lt. Jim Gordon and District Attorney Harvey Dent, Batman sets out to dismantle the remaining criminal organizations that plague the streets. The partnership proves to be effective, but they soon find themselves prey to a reign of chaos unleashed by a rising criminal mastermind known to the terrified citizens of Gotham as the Joker.130.643/qJ2tW6WMUDux911r6m7haRef0WH.jpgWelcome to a world without rules.Drama, Action, Crime, ThrillerDC Comics, Legendary Pictures, Syncopy, Isobel Griffiths, Warner Bros. PicturesUnited Kingdom, United States of AmericaEnglish, Mandarinjoker, sadism, chaos, secret identity, crime fighter, superhero, anti hero, scarecrow, based on comic, vigilante, organized crime, tragic hero, anti villain, criminal mastermind, district attorney, super power, super villain, neo-noir
319995Avatar7.57329815Released2009-12-152923706026162False/vL5LR6WdxWPjLPFRLe133jXWsh5.jpg237000000https://www.avatar.com/movies/avatartt0499549enAvatarIn the 22nd century, a paraplegic Marine is dispatched to the moon Pandora on a unique mission, but becomes torn between following orders and protecting an alien civilization.79.932/kyeqWdyUXW608qlYkRqosgbbJyK.jpgEnter the world of Pandora.Action, Adventure, Fantasy, Science FictionDune Entertainment, Lightstorm Entertainment, 20th Century Fox, Ingenious MediaUnited States of America, United KingdomEnglish, Spanishfuture, society, culture clash, space travel, space war, space colony, tribe, romance, alien, futuristic, space, alien planet, marine, soldier, battle, love affair, nature, anti war, power relations, joyful
424428The Avengers7.71029166Released2012-04-251518815515143False/9BBTo63ANSmhC4e6r62OJFuK2GL.jpg220000000https://www.marvel.com/movies/the-avengerstt0848228enThe AvengersWhen an unexpected enemy emerges and threatens global safety and security, Nick Fury, director of the international peacekeeping agency known as S.H.I.E.L.D., finds himself in need of a team to pull the world back from the brink of disaster. Spanning the globe, a daring recruitment effort begins!98.082/RYMX2wcKCBAr24UyPD7xwmjaTn.jpgSome assembly required.Science Fiction, Action, AdventureMarvel StudiosUnited States of AmericaEnglish, Hindi, Russiannew york city, superhero, shield, based on comic, alien invasion, superhero team, aftercreditsstinger, duringcreditsstinger, marvel cinematic universe (mcu)
5293660Deadpool7.60628894Released2016-02-09783100000108False/en971MEXui9diirXlogOrPKmsEn.jpg58000000https://www.20thcenturystudios.com/movies/deadpooltt1431045enDeadpoolThe origin story of former Special Forces operative turned mercenary Wade Wilson, who, after being subjected to a rogue experiment that leaves him with accelerated healing powers, adopts the alter ego Deadpool. Armed with his new abilities and a dark, twisted sense of humor, Deadpool hunts down the man who nearly destroyed his life.72.735/zq8Cl3PNIDGU3iWNRoc5nEZ6pCe.jpgWitness the beginning of a happy ending.Action, Adventure, Comedy20th Century Fox, The Donners' Company, Genre FilmsUnited States of AmericaEnglishsuperhero, anti hero, mercenary, based on comic, aftercreditsstinger, duringcreditsstinger
6299536Avengers: Infinity War8.25527713Released2018-04-252052415039149False/mDfJG3LC3Dqb67AZ52x3Z0jU0uB.jpg300000000https://www.marvel.com/movies/avengers-infinity-wartt4154756enAvengers: Infinity WarAs the Avengers and their allies have continued to protect the world from threats too large for any one hero to handle, a new danger has emerged from the cosmic shadows: Thanos. A despot of intergalactic infamy, his goal is to collect all six Infinity Stones, artifacts of unimaginable power, and use them to inflict his twisted will on all of reality. Everything the Avengers have fought for has led up to this moment - the fate of Earth and existence itself has never been more uncertain.154.340/7WsyChQLEftFiDOVTGkv3hFpyyt.jpgAn entire universe. Once and for all.Adventure, Action, Science FictionMarvel StudiosUnited States of AmericaEnglish, Xhosasacrifice, magic, superhero, based on comic, space, battlefield, genocide, magical object, super power, aftercreditsstinger, marvel cinematic universe (mcu), cosmic
7550Fight Club8.43827238Released1999-10-15100853753139False/hZkgoQYus5vegHoetLkCJzb17zJ.jpg63000000http://www.foxmovies.com/movies/fight-clubtt0137523enFight ClubA ticking-time-bomb insomniac and a slippery soap salesman channel primal male aggression into a shocking new form of therapy. Their concept catches on, with underground "fight clubs" forming in every town, until an eccentric gets in the way and ignites an out-of-control spiral toward oblivion.69.498/pB8BM7pdSp6B6Ih7QZ4DrQ3PmJK.jpgMischief. Mayhem. Soap.DramaRegency Enterprises, Fox 2000 Pictures, Taurus Film, Atman Entertainment, Knickerbocker Films, The Linson Company, 20th Century FoxUnited States of AmericaEnglishdual identity, rage and hate, based on novel or book, nihilism, fight, support group, dystopia, insomnia, alter ego, breaking the fourth wall, split personality, quitting a job, dissociative identity disorder, self destructiveness
8118340Guardians of the Galaxy7.90626638Released2014-07-30772776600121False/uLtVbjvS1O7gXL8lUOwsFOH4man.jpg170000000http://marvel.com/guardianstt2015381enGuardians of the GalaxyLight years from Earth, 26 years after being abducted, Peter Quill finds himself the prime target of a manhunt after discovering an orb wanted by Ronan the Accuser.33.255/r7vmZjiyZw9rpJMQJdXpjgiCOk9.jpgAll heroes start somewhere.Action, Science Fiction, AdventureMarvel StudiosUnited States of AmericaEnglishspacecraft, based on comic, space, orphan, adventurer, aftercreditsstinger, duringcreditsstinger, marvel cinematic universe (mcu)
9680Pulp Fiction8.48825893Released1994-09-10213900000154False/suaEOtk1N1sgg2MTM7oZd2cfVp3.jpg8500000https://www.miramax.com/movie/pulp-fiction/tt0110912enPulp FictionA burger-loving hit man, his philosophical partner, a drug-addled gangster's moll and a washed-up boxer converge in this sprawling, comedic crime caper. Their adventures unfurl in three stories that ingeniously trip back and forth in time.74.862/d5iIlFn5s0ImszYzBPb8JPIfbXD.jpgJust because you are a character doesn't mean you have character.Thriller, CrimeMiramax, A Band Apart, Jersey FilmsUnited States of AmericaEnglish, Spanish, Frenchdrug dealer, boxer, massage, stolen money, briefcase, crime boss, redemption, heirloom, dance competition, los angeles, california, theft, nonlinear timeline, multiple storylines, neo-noir, hilarious
idtitlevote_averagevote_countstatusrelease_daterevenueruntimeadultbackdrop_pathbudgethomepageimdb_idoriginal_languageoriginal_titleoverviewpopularityposter_pathtaglinegenresproduction_companiesproduction_countriesspoken_languageskeywords
1177888753310Consuelita0.00Released1925-08-01060FalseNaN0NaNtt0166542itVoglio a Tte!Consuelita, a young woman who longs to escape the harsh conditions of her small fishing village, is married off to a wealthy, mentally ill Englishman. (Melo)drama ensues.0.627/fZ88FrtqsJXdrCljOZGgkXcdAgf.jpgNaNNaNNaNItalyNo LanguageNaN
1177889753312After An Autumn Day That Felt Like Summer0.00Released2003-06-21015FalseNaN5000https://vimeo.com/1342717tt0393029enAfter An Autumn Day That Felt Like SummerSeptember 11th has left Ellsworth a shell-shocked mess. Not only is he struggling to process his feelings about the event, but he is unable to return to a normal life and his relationship with his live-in girlfriend Eleanor is suffering. After returning to the Manhattan street corner where he witnessed the horrific attack, Ellsworth visits Anne, the woman with whom he is having an affair. His questioning of everything that Americans cherish is met with disinterest by Anne, who leaves to rehearse a fan dance with her burlesque company. Returning home, Anne and Ellsworth are confronted by Eleanor. Unwilling to converse or compromise, Eleanor demands that he instantly choose between them.0.600/njDpLQhVx8Xj93WzIiiZfNkcRcn.jpgIn the wake of 9-11, one man struggles to get his life back on track.DramaNaNUnited States of AmericaEnglishNaN
1177890753313Mon Chinois0.00ReleasedNaT00FalseNaN0NaNNaNenMon ChinoisThis short film seeks to identify in a humorous way general stereotypes and archetypes associated with chinese or asian.0.600/rldbES5DWzyZy85EZuaVorivfoi.jpgNaNNaNNaNNaNNaNNaN
1177891753314Expressions0.00Released1971-01-01023FalseNaN0NaNNaNfrExpressionsNaN0.600/lFuAoAq1wLwtFHuBgLl5yvv0d2i.jpgNaNNaNNaNFranceNo LanguageNaN
1177892753316Her0.00Released1969-03-2105FalseNaN0NaNNaNenHer"Her was shot as my contributionto a collective film of the Italian Film-makers' Cooperative, Tutto,tutto nello stesso istante, whichstarted out as a Dadaist protestagainst police brutality. I used a "Newsweek" cutting about the Chicago Convention riots, about a woman being beaten up, and isolated in every line a symbolic word, which returns in the second part with anextension of its original meaning. I remember showing it with an 8mm projector at the USIS Rome Library in winter 1970 as part of a concertof American music." Massimo Bacigalupo0.600/rjf3pdsK7CmQASzKdRhUtYcv5Km.jpgNaNNaNNaNItalyNo LanguageNaN
1177893753317Lilian0.00Released1965-01-0109FalseNaN0NaNNaNitLilianThis short film was timed to Midsömmer, a lyrical track in the Atlantic album The Modern Jazz Quartet at Music Inn/Volume 2. The heroine reconciles herself with the breakup of an affair.0.600NaNNaNNaNNaNItalyNo LanguageNaN
1177894753318Virginal Young Blondes0.00Released2004-05-15016FalseNaN5000https://vimeo.com/1324875tt0438562enVirginal Young BlondesUnemployed John goes to a bar, where he meets Sofia, who mistakes him for a trust-fund brat and offers her sexual services for money. John doesn't bother to dispel Sofia's misconceptions and accepts her invitation to get stoned. As Sofia and John pass "the most expensive chocolate shop in the world," both are captivated by the cakes in the windows. He is stunned when the amount comes to $42.50. On the Brooklyn Bridge, Sofia shares a traumatic incident from her past in which her drug dealer boyfriend was murdered in front of her and she was raped by the killers. Recomposing herself, Sofia leaves and John, in his drugged state, devours the cakes.0.600/aK6mPWkhJxooUR5PK72CaiyDzYI.jpgThe biggest secrets are often those learned by accidentDramaNaNUnited States of AmericaEnglishNaN
1177895753319Ariel loquitur0.00Released1967-01-01050FalseNaN0NaNNaNitAriel loquiturMaterial shot between 1961 and 1967 ,including bad takes for Quasi una tangente, is reorganized following the five acts of Shakespeare's The Tempest. Thus Ariel loquitur ("Ariel speaks") has five numbered sections, and a Prospero-like figure of old philosopher appears repeatedly. The wedding ceremony of Miranda and Ferdinand in Act IV of the play is performed in section IV, an unedited night-film in which one catches glimpses of a match being lit. The last section introduces color and sound, the latter through the Beatles' A Day in the Life (from Sgt.Pepper’s Lonely Hearts Club Band).0.600/dcRSUglRCWRRBvgQskzC9bbvsjY.jpgNaNNaNNaNItalyNo LanguageNaN
1177896753320Paphos0.00Released1970-12-3106FalseNaN0NaNNaNenPaphosA sketch of materials (and texts) that were to be used in Nor Wood and Migration, this short film has the freshness of an improvisation.0.600NaNNaNNaNNaNItalyNo LanguageNaN
117789714336295 SHORT STORIES0.00Released2024-09-18016FalseNaN0NaNNaNfr5 HISTOIRES COURTESUnfolding during one night in Barbès, we peek in the lives of a clumsy delivery man, exes coming back, the strange side of internet fame, a stewardess desperate for a hairdresser, and best friends with a crush.1.034NaNFive short stories, unfolding during one night in Barbès.Drama, ComedyNaNFranceEnglish, FrenchNaN

Duplicate rows

Most frequently occurring

idtitlevote_averagevote_countstatusrelease_daterevenueruntimeadultbackdrop_pathbudgethomepageimdb_idoriginal_languageoriginal_titleoverviewpopularityposter_pathtaglinegenresproduction_companiesproduction_countriesspoken_languageskeywords# duplicates
321192957Soldiers From Eastern Europe 130.00Released2005-10-120114TrueNaN0NaNNaNenSoldiers From Eastern Europe 13Another combat training session gone suck-cessful! Join Eastern Euro-soldiers as they hit the training facilities for more hardcore sexual man-action!0.0/3miaWnx10YRplzPW3CDOjC1MGoE.jpgNaNNaNEagle VideoCzech RepublicNaNNaN4
551199214Last Laughs0.00Released2023-05-28047FalseNaN0NaNNaNenLast LaughsFarewell the Comedy Festival for another year in one glorious night out at SkyCity Theatre! Grab your comedy-loving mates and be a part of the magic as we announce the winners of the prestigious Billy T and Fred Awards, and celebrate the very best of the Fest - all in one show.     Hosted by Chris Parker and featuring headliner Michèle A'Court.0.0NaNNaNNaNNaNNaNEnglishNaN4
761205264Hopeless: The Film0.00Released2023-09-30052TrueNaN0NaNNaNenHopeless: The FilmHopeless stars Casey Calvert and Lumi Ray as best friends whose relationship metamorphoses into something unexpected - and extraordinary - when a devastated Casey turns to Lumi for comfort after a painful breakup.0.0NaNNaNRomanceHolly Randall ProductionsNaNNaNlesbian relationship4
811206572Dude, Don't Fuck My Wife 30.00Released2014-12-150143TrueNaN0NaNNaNenDude, Don't Fuck My Wife 3C'mon man, leave my wife alone! The husbands beg and beg but dudes won't stop fucking their wives. It's a shame. These powerless cuckolds can do nothing but watch as hung lovers and side pieces fuck their wives well right before their very eyes. The wives are unhappy until they get more cock in their pussy. These husbands can't bear to watch but they just can't stop looking.0.0/336ojave64saSsHKwakJorbH72u.jpgNaNNaNNaughty SinnerUnited States of AmericaNaNNaN4
1121213633My Sister Is Wet & Horny0.00Released2014-10-060100TrueNaN0NaNNaNenMy Sister Is Wet & HornyA family that lays together stays together! They aren't so little anymore! They've grown up to be so sweet, so wet, so horny and willing to do whatever it takes to keep that big dick in the family! When Isabella De Santos got a look at Ralph's dick pic on twitter she couldn't wait to see how many licks it takes to get every last gooey drop out of his monster cock! Tony came home from college for summer and found Kacey living in his bedroom, they are going to have to share, and guess what? There will be no bunk beds this time! Sandra didn't want Brad to tell everybody from the Old Country about her pussy pies.0.0/jCxYKTIDfYEQJNZ4xcFxgJmJo80.jpgNaNNaNLethal HardcoreNaNNaNNaN4
1451221745Last Day0.00ReleasedNaT038TrueNaN0NaNNaNenLast Dayno description yet ...0.0NaNNaNNaNNaNNaNNaNNaN4
1621224655Don't Break Me 390.00ReleasedNaT0155TrueNaN0NaNNaNenDon't Break Me 39Jackie Hoff gets fucked hard by J-Mac. Hot Latina Maya Farrel graves J-Mac's hard dick. Rachel Starr loves fucking more than anything. Petite Payton Avery takes on J-Mac's thick dick. Catalina Ossa gets her trimmed pussy pounded.0.0/35FuFb0B1WzaE80gYKcpJen4b5G.jpgNaNNaNNaNNaNNaNNaN4
1631224661Mr. Roberts0.00ReleasedNaT033FalseNaN0NaNNaNenMr. RobertsIn "Mr. Roberts", written by Terrence McNally and staring Jonathan Taylor Thomas and Steven Weber, a teacher in a 1970's classroom struggles with his closeted gay status and a student who is on the verge of coming out of the closet.0.0NaNNaNNaNNaNNaNNaNNaN4
2061235259Gogo no Kouchou: Junai Mellow yori0.00Released2012-09-21030TrueNaN0NaNNaNja午後の紅潮 ~純愛メロウより~NaN0.0NaNNaNAnimationNaNJapanJapanesehentai4
2251240115My Pretty Cospet 20.00Released2004-01-0100TrueNaN0NaNNaNesMy Pretty Cospet 2NaN0.0/3FkkHtybRMfsOJxzYyc4M3GLPQ3.jpgNaNNaNNaNJapanNaNNaN4